HopBox: An image analysis pipeline to characterize hop cone morphology
[1];
[2];
- USDA‐ARS Forage Seed and Cereal Research Unit Prosser Washington USA
- USDA‐ARS Northwest Sustainable Agroecosystems Research Unit Prosser Washington USA
- Oak Ridge Institute for Science and Education Prosser Washington USA
- Department of Biological and Agricultural Engineering University of California Davis California USA
- USDA‐ARS Horticultural Crops Production and Genetic Improvement Research Unit Prosser Washington USA
Abstract Hop cone morphology can influence picking and drying ability, and color can impact consumer preference and may be indicative of quality. However, these characteristics are not generally evaluated in hop breeding programs due to the tedious nature of trait quantification and the extensive variation among cones within a genotype. We developed the HopBox, which is a simply constructed light box with a camera mount, and a publicly available image processing pipeline that identifies hop cones within color‐corrected images, reads a QR code within the image, and outputs data on hop cone length, width, area, perimeter, openness, weight, color, and density. The trained model was applied to images of 500 cones each from 15 replicated advanced hop genotypes from the USDA‐ARS breeding program in Prosser, Washington. Analysis of variance revealed significant ( p < 0.001) differences between genotypes for all traits measured, enabling breeders to discriminate between genotypes for selection purposes. Broad sense heritability for all traits ranged from 0.23 to 0.59. A random sampling of hop cones from the complete dataset revealed that imaging only 5–10 cones adequately captured genotypic variation and provided acceptable rank correlations ( r s > 0.75); however, increasing the sample size to 30 provided optimal precision. Instructions for constructing a HopBox and the code for the analysis pipeline are publicly available online and have wide applicability for hop breeding and research.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 1996439
- Journal Information:
- Plant Phenome Journal, Journal Name: Plant Phenome Journal Journal Issue: 1 Vol. 6; ISSN 2578-2703
- Publisher:
- Wiley Blackwell (John Wiley & Sons)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Accurate determination of genotypic variance of cell wall characteristics of a Populus trichocarpa pedigree using high-throughput pyrolysis-molecular beam mass spectrometry
Morphophysiological Plant Phenotyping for the Development of Plant Breeding Under Drought and Heat Conditions: A Practical Approach